The interaction between T cells, particularly naïve CD4 T cells (CD4Tn), and colorectal cancer (CRC) is highly complex. CD4Tn play a crucial role in modulating immune responses within the tumor microenvironment, yet the precise mechanisms by which they influence tumor progression remain elusive. This study aims to explore the relationship between CRC and CD4Tn, identify biomarkers and therapeutic targets, and focus on the role of CD4Tn in shaping the immune environment of CRC. Single-cell transcriptomics, alongside the scPagwas algorithm, were employed to identify pivotal T cell subsets involved in CRC progression. Bulk transcriptomic data were further analyzed using deconvolution algorithms to elucidate the roles of these key T cell subsets. The abundance of naïve CD4 T cells (CD4Tn) was specifically assessed to gauge patient responses to immunotherapy, alterations in the immune microenvironment, and correlations with genetic mutations. Key genes linked to CD4Tn were identified using weighted gene co-expression network analysis and Pearson correlation scores. The SMR algorithm was subsequently used for validation, with experimental verification following. Through single-cell transcriptomics and the scPagwas algorithm, CD4Tn was confirmed as a critical cell type in CRC progression. High infiltration of CD4Tn cells in CRC patients was correlated with poorer prognosis and suboptimal responses to immunotherapy. SMR analysis suggested a potential causal link between DRAM2 gene expression and CRC progression. Experimental knockdown of DRAM2 in colorectal cancer cells significantly inhibited tumor growth. The DRAM2 gene, associated with CD4Tn cells, appears to play a pivotal role in the advancement of CRC and may represent a promising therapeutic target for treatment.

Ferroptosis is a novel form of programmed cell death that is triggered by iron-dependent lipid peroxidation. Brusatol (BRU), a natural nuclear factor erythroid 2-related factor 2 inhibitor, exhibits potent anticancer effects in various types of cancer. However, the exact mechanism of BRU in the treatment of hepatocellular carcinoma (HCC) remains unknown. The anticancer effects of BRU in HCC were detected using cell counting kit-8 and colony formation assays and a xenograft model. RNA sequencing (RNA-seq) and bioinformatics analyses of HCC cells were utilized to elucidate the mechanism underlying the effects of BRU in HCC. The levels of reactive oxygen species (ROS), glutathione (GSH), malondialdehyde (MDA), and Fe 2+ were measured using assay kits. The expression of activating transcription factor 3 (ATF3) was tested using RT-qPCR, western blotting, and immunofluorescence staining. The role of ATF3 in BRU-induced ferroptosis was examined using siATF3. BRU significantly inhibited HCC cell proliferation, both in vitro and in vivo. BRU activated the ferroptosis signaling pathway and increased ATF3 expression. Furthermore, ATF3 knockdown impeded BRU-induced ferroptosis. BRU suppressed HCC growth through ATF3-mediated ferroptosis, supporting BRU as a promising therapeutic agent for HCC.

ObjectiveThe relationship between macrophages and the gut microbiota in patients with atherosclerosis remains poorly defined, and effective biological markers are lacking. This study aims to elucidate the interplay between gut microbial communities and macrophages, and to identify biomarkers associated with the destabilization of atherosclerotic plaques. The goal is to enhance our understanding of the underlying molecular pathways and to pave new avenues for diagnostic approaches and therapeutic strategies in the disease.MethodsThis study employed Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis on atherosclerosis datasets to identify macrophage-associated genes and quantify the correlation between these genes and gut microbiota gene sets. The Random Forest algorithm was utilized to pinpoint PLEK, IRF8, BTK, CCR1, and CD68 as gut microbiota-related macrophage genes, and a nomogram was constructed. Based on the top five genes, a Non-negative Matrix Factorization (NMF) algorithm was applied to construct gut microbiota-related macrophage clusters and analyze their potential biological alterations. Subsequent single-cell analyses were conducted to observe the expression patterns of the top five genes and the interactions between immune cells. Finally, the expression profiles of key molecules were validated using clinical samples from atherosclerosis patients.ResultsUtilizing the Random Forest algorithm, we ultimately identified PLEK, IRF8, CD68, CCR1, and BTK as gut microbiota-associated macrophage genes that are upregulated in atherosclerotic plaques. A nomogram based on the expression of these five genes was constructed for use as an auxiliary tool in clinical diagnosis. Single-cell analysis confirmed the specific expression of gut microbiota-associated macrophage genes in macrophages. Clinical samples substantiated the high expression of PLEK in unstable atherosclerotic plaques.ConclusionGut microbiota-associated macrophage genes (PLEK, IRF8, CD68, CCR1, and BTK) may be implicated in the pathogenesis of atherosclerotic plaques and could serve as diagnostic markers to aid patients with atherosclerosis.

Purpose: Due to poor prognosis and immunotherapy failure of skin cutaneous melanoma (SKCM), this study sought to find necroptosis-related biomarkers to predict prognosis and improve the situation with predicted immunotherapy drugs. Experimental Design: The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression Program (GTEx) database were utilized to recognize the differential necroptosis-related genes (NRGs). Univariate Cox (uni-Cox) and least absolute shrinkage and selection operator (LASSO) Cox analysis were utilized for prognostic signature establishment. The signature was verified in the internal cohort. To assess the signature's prediction performance, the area under the curve (AUC) of receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) analyses, multivariate Cox (multi-Cox) regression, nomogram, and calibration curves were performed. The molecular and immunological aspects were also reviewed using single-sample gene set enrichment analysis (ssGSEA). Cluster analysis was performed to identify the different types of SKCM. Finally, the expression of the signature gene was verified by immunohistochemical staining. Results: On basis of the 67 NRGs, 4 necroptosis-related genes (FASLG, PLK1, EGFR, and TNFRSF21) were constructed to predict SKCM prognosis. The area's 1-, 3-, and 5-year OS under the AUC curve was 0.673, 0.649, and 0.677, respectively. High-risk individuals had significantly lower overall survival (OS) compared to low-risk patients. Immunological status and tumor cell infiltration in high-risk groups were significantly lower, indicating an immune system that was suppressed. In addition, hot and cold tumors could be obtained by cluster analysis, which is helpful for accurate treatment. Cluster 1 was considered a hot tumor and more susceptible to immunotherapy. Immunohistochemical results were consistent with positive and negative regulation of coefficients in signature. Conclusion: The results of this finding supported that NRGs could predict prognosis and help make a distinction between the cold and hot tumors for improving personalized therapy for SKCM.

Background: The objective is to create an IRGPI (Immune-related genes prognostic index), which could predict the survival and effectiveness of immune checkpoint inhibitor (ICI) treatment for lung adenocarcinoma (LUAD).Methods: By applying weighted gene co-expression network analysis (WGCNA), we ascertained 13 genes associated with immune functions. An IRGPI was constructed using four genes through multicox regression, and its validity was assessed in the GEO dataset. Next, we explored the immunological and molecular attributes and advantages of ICI treatment in subcategories delineated by IRGPI. The model genes were also validated by the random forest tree, and functional experiments were conducted to validate it.Results: The IRGPI relied on the genes CD79A, IL11, CTLA-4, and CD27. Individuals categorized as low-risk exhibited significantly improved overall survival in comparison to those classified as high-risk. Extensive findings indicated that the low-risk category exhibited associations with immune pathways, significant infiltration of CD8 T cells, M1 macrophages, and CD4 T cells, a reduced rate of gene mutations, and improved sensitivity to ICI therapy. Conversely, the higher-risk group displayed metabolic signals, elevated frequencies of TP53, KRAS, and KEAP1 mutations, escalated levels of NK cells, M0, and M2 macrophage infiltration, and a diminished response to ICI therapy. Additionally, our study unveiled that the downregulation of IL11 effectively impedes the proliferation and migration of lung carcinoma cells, while also inducing cell cycle arrest.Conclusion: IRGPI is a biomarker with significant potential for predicting the effectiveness of ICI treatment in LUAD patients and is closely related to the microenvironment and clinicopathological characteristics.

Berberine hydrochloride (BBR) could inhibit the proliferation, migration, and invasion of various cancer cells. As the only enzyme for the de novo synthesis of ribonucleotides, RRM2 is closely related to the development of tumorigenesis. However, not much is currently known about the functional roles of RRM2 in breast cancer (BRCA), and whether BBR regulates the migration and invasion of BRCA cells by regulating the expression of RRM2 remains to be determined. We study the effects of BBR on BRCA cell proliferation in vitro and tumorigenesis in vivo by using colony formation assays, EdU assays, and xenograft models. Transcriptome sequencing, the random forest algorithm, and KEGG analysis were utilized to explore the therapeutic target genes and relative pathways. The expression of RRM2 in BRCA patients was analyzed with The Cancer Genome Atlas (TCGA) dataset, the GEPIA website tool, the Gene Expression Omnibus (GEO) database, and the UALCAN database. The survival probability of BRCA patients could be predicted by survival curve and nomogram analysis. Molecular docking was used to explore the affinity between BBR and potential targets. Gain- and loss-of-function methods were employed to explore the biological process in RRM2 participants. We comprehensively investigated the pharmacological characteristics of BBR on BRCA cell lines and discovered that BBR could inhibit the proliferation of BRCA cells in vitro and in vivo. Combining transcriptome sequencing and KEGG analysis, we found that BBR mainly affected the biological behavior of BRCA cells via HIF-1α and AMPK signal pathways. Additionally, by using bioinformatics and molecular docking, we demonstrated that RRM2 plays an oncogenic role in BRCA samples and that it acts as the hub gene of BBR on BRCA cells. Knockdown and overexpression studies indicated that RRM2 promoted BRCA cell migration as well as invasion in vitro by affecting the epithelial-to-mesenchymal transition (EMT). Our study demonstrated the significance of BBR regulating HIF-1α and AMPK signaling pathways in BRCA cells. Moreover, we revealed the carcinogenic role and potential mechanism of RRM2 as a core regulatory factor of BBR in BRCA in controlling BRCA invasion, migration, and EMT, suggesting that RRM2 may be a therapeutic target and prognostic biomarker for BRCA therapy.

Background:Osteoarthritis (OA) is a common joint disease with long-term pain and dysfunction that negatively affects the quality of life of patients. Neutrophil extracellular traps (NETs), consisting of DNA, proteins and cytoplasm, are released by neutrophils and play an important role in a variety of diseases. However, the relationship between OA and NETs is unclear.Methods:In our study, we used bioinformatics to explore the relationship between OA and NETs and the potential biological markers. GSE55235, GSE55457, GSE117999 and GSE98918 were downloaded from the Gene Expression Omnibus (GEO) database for subsequent analysis.After differential analysis of OA expression matrices, intersection with NET-related genes (NRGs) was taken to identify Differentially expressed NRGs (DE-NRGs) in OA processes. Evaluation of immune cell infiltration by ssGSEA and CIBERSORT algorithm. The GSVA method was used to analyze the activity changes of Neutrophils pathway, Neutrophil degranulation and Neutrophil granule constituents pathway.Results:Based on RandomForest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) learning algorithms, five core genes (CRISPLD2, IL1B, SLC25A37, MMP9, and TLR7) were identified to construct an OA-related nomogram model for predicting OA progression. ROC curve results for these genes validated the nomogram's reliability. Correlation analysis, functional enrichment, and drug predictions were performed for the core genes. TLR7 emerged as a key focus due to its high importance ranking in RF and SVM-RFE analyses. Gene Set Enrichment Analysis (GSEA) revealed a strong association between TLR7 and the Neutrophil extracellular trap pathway. Expression of core genes was demonstrated in mice OA models and human OA samples. TLR7 expression in ATDC5 cell line was significantly higher than control after TNFα induction, along with increased IL6 and MMP13.Conclusion:TLR7 may be related to NETs and affects OA.

Objective: To investigate the injury of cyanate on the pulmonary function and morphology of C57/BL6N mice. Methods: Forty male C57/BL6N mice were randomly divided into two groups: normal control group（20 mice） and cyanate group（20 mice）. Mice were exposed to 100 mmol/L cyanate feeding for 4 weeks, and pulmonary Raw（Resistance in Air Way） was measured at the beginning and end of the experiment. The mice were sacrificed at the end of the fourth week of the experiment, and the lung tissues were collected for pathological observation and molecular detection of E-Cadherin and Fibronectin. Well-growing A549 cells in logarithmic growth phase were treated with cyanate at the concentrations of 0, 0.25, 0.5 and 1 mmol/L for 24 h, and the cell viability was detected by CCK8 method; reactive oxygen species ROS fluorescent probe（DCFH-DA） was used to detect the changes of ROS levels, and expressions of E-Cadherin and Fibronectin in cells and pulmonary tissues were detected by Western blot. Results: At the beginning of the experiment, the pulmonary airway resistance values of the mice in the normal control group and the cyanate group were（1.82±0.76）cmH 2 O/（L·s） and（1.85±0.78）cmH 2 O/（L·s）, respectively, with no significant difference. Four weeks later, the pulmonary airway resistance value of mice in the cyanate group was increased to（4.86±0.87）cmH 2 O/（L·s）（P＜0.01）. The HE staining showed that, compared with the normal control group, the injured alveolar structure, the thickened tracheal wall and the significantly proliferated pulmonary interstitial tissue were observed in the cyanate group. The Masson staining showed that elastic fibers were deposited around the trachea of mice in the cyanate group. The results of CCK8 assay for the viability of A549 cells showed that 0.5 mmol/L cyanate exposure could reduce the viability（P＜0.01）. The immunofluorescence staining showed that cyanate could increase ROS level in A549 cells by producing green fluorescence in a concentration-dependent manner. The results of Western blotting showed that 0.5 mmol/L of cyanate treatment on A549 cells could reduce the expression of E-Cadherin（P＜0.01） with increasing concentration of cyanate. The expression level of Fibronectin in A549 cells was increased with the increasing cyanate concentration, and there was a significant difference（P＜0.01） on 1 mmol/L cyanate. Western blot results of lung showed the decreasing expression of E-Cadherin（P＜0.01） and increasing expression of Fibronectin（P＜0.01） in cyanate mice. Conclusion: Pathological concentrations of cyanate can induce the proliferation of pulmonary interstitial tissue, fibrous deposition, and increased pulmonary airway resistance in mice, which may be related to damaged pulmonary epithelial cell viability, enhanced ROS production, and induced pathologic changes of extracellular matrix by cyanate.

Brusatol (BRU) is an important compound extracted from Brucea javanica oil, whose pharmacological effects are able to induce a series of biological effects, including inhibition of tumor cell growth, anti-inflammatory, antiviral, and antitumor. Currently, there are so few studies about the brusatol effects on colorectal cancer that its anticancer mechanism has not been clearly defined. In this study, we made an in-depth investigation into the brusatol effect towards the proliferation and metastasis of colon cancer and the possible mechanism. The inhibitory effect of BRU on the proliferation of colorectal cancer cells was unveiled via CCK-8 method and colony formation assay, while the inhibitory effect of BRU on migration and invasion of colorectal cancer cells was revealed by scratch assay and transwell assay. In addition, Western blot results also revealed that BRU inhibited not only the expressions of RhoA and ROCK1 but also the protein expressions of EMT-related markers e-cadherin, N-cadherin, Vimentin, MMP2, and MMP9 in colon cancer cells. Through the xenotransplantation model, our in vivo experiment further verified the antitumor effect of BRU on colon cancer cells in vitro, and the results were consistent with the protein expression trend. In conclusion, BRU may inhibit the proliferation and metastasis of colorectal cancer by influencing EMT through RhoA/ROCK1 pathway.

Background To establish a pyroptosis-related gene (PRG) signature that could be utilized to predict hepatocellular carcinoma (HCC) survival and clinical features. Methods The Cancer Genome Atlas (TCGA) database was utilized to identify differentially expressed PRGs. Univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were utilized to establish the prognostic signature. The signature was verified in the International Cancer Genome Consortium cohort (ID: LIHC-US). Based on the medium-risk score, HCC samples were classified into high- or low-risk subgroups. For signature accuracy prediction, we utilized receiver operating characteristic (ROC) analysis and the Kaplan-Meier estimate (K-M). Molecular and immunological aspects were also reviewed using single-sample gene set enrichment analysis (ssGSEA). Finally, quantitative real-time PCR (qRT-PCR) was utilized to verify the expression of hub genes in vitro. Results On basis of the 33 PRGs, five PRGs (CASP8, GSDMC, NLRP6, NOD2, and PLCG1) were identified that could predict HCC prognosis. Individuals with high-risk scores had significantly lower overall survival (OS) compared to those with low-risk scores. To assess and confirm this signature’s prediction performance, the area under the curve (AUC) of ROC curves was utilized. In multivariate analysis, the risk score was proven to be a significant independent prognostic factor. Immunological status and tumor cell infiltration in high-risk groups were both significantly greater than in low-risk groups, indicating that the immune system was more activated. qRT-PCR analysis demonstrated that the five PRGs in HCC cell lines were differently expressed in the prognostic signature. Conclusions The signature could precisely predict survival outcomes and reveal immune microenvironment composition, as well as strengthen the argument for more credible clinical and functional research in HCC patients.